2. Information overload syndrome
• I just can’t keep together all I
find on the Web
• I get tons of mails, links,
comments, suggestions, ...
• huge quantity = no quality
4. Bad effects
• cannot filter cool / important things
from garbage / unwanted
(ai / statistical / ads / from unknown
sources)
• get a lot of useless suggestions -
not enough great suggestions
• forget relations between things
6. What I should expect
• get only relevant suggestions /
content / links, pertaining to my life,
actions, interests, friends
• take more into consideration
suggestions or content from friends /
trusted people / people with similar
interests
7. I’m the one who defines what I like
• extract some content (text, pictures,
video, audio)
• place it into my world
• link it in a personal way to other things
I have chosen
• describe it with words, comments in a
well-defined and searchable way
8. How I try to do it now
• del.icio.us and twine to organize
content (social bookmarking)
• friendfeed, twitter
(monodirectional / trust) and
facebook (bidirectional / friend)
to get new content (social
suggestions)
9. Why this is not enough
• del.icio.us: conceptsurl and adefined (tags), no
relations between an
loosely
concept, within urls,
within concepts
• twine: flat list ofand little conceptualization for each
del.icio.us-like urls
twines (only clustered by similarity),
twine
• twitter: scattered urls posted with everything else up
conceptualization and relations
by gurus,
to me
• without relations / conceptualization
friendfeed: urls aggregated from different services
• only from friends
facebook: content without any conceptualization and
• all: only urls, no anonymous content inside the page
10. 99 ways allows me to:
• select just what I like (text, image, video, audio)
and add it as a node of my graph
• describe each node with concepts and properties
univocally defined and universally recognized in
the Web of Data
• set personal links / relations (= links with a
universally recognized meaning) among nodes as
arches in my graph
• browse the Web guided by what I (and the
others) chose
14. Resource description
• I want to describe each node with the proper
richness but also to leave it anonymous
• the mere placement in my graph is already a
description of the resource (through the
relationships with the existent nodes)
• so I can search / browse my graph by
concept / property / smart tag
• this is my high-quality web
16. What if everybody does the same?
• there will be innumerable personal and well-
selected views of the Web
• in contact with one another by common
content / concepts
• particular attention to my friends’ graphs
• I may be curious to know what a particular
friend of mine, with those particular
interests, likes and chose
18. How can I get value from others’ views?
• find new content related to what I like
• find new interesting / trusted content
independently from what I like
• find new interesting people (on the
basis of my graph)
20. Contact points between me and you
• same chosen content
• my content described with the same concepts
as your content (recognizable thanks to the
semantics hook)
• I may be interested in what else you linked
from / to our contact point
• we may want to become friends if we have a
lot of content / concepts in common
24. Web+
• How does this ‘sense enrichment’ made by me
and the others affect my ordinary web
browsing?
• page content fruition guided by things
already inserted in graphs: highlighted
content + who chose it + the best graphs’
links from that node + other info
• hyperlinks made ’to talk’: they say how much
they lead to chosen content + other info
27. Indirect graph population
• But what about the other services I use? I don’t
want to lose them
• I can add something to my graph through:
• del.icio.us: to solve the cold start problem
• facebook (activity streams): to keep track of my
actions on the web (into ‘activity’ nodes)
• twitter: to send new content nodes / comments
(optionally described with #tags as concepts)
to some friends
29. The 99ways - Web of Data
symbiosis
• the Web of Data provides 99ways with
unambiguous URIs about instances /
concepts / properties / relations
• 99ways provides the Web of Data with
more and more web resources linked to
these URIs
30. 99ways: what is it?
+
A bookmarklet you An extension
drag into your installed in
browser toolbar your browser
Tools
99
99ways >
31. Proactive approach
• When you find something interesting on the
web, whatever it is (text, image, video, ...):
• click on the 99 button and select the
desired content
• save it as a node of your graph (YOW)
• link it to/from other existing nodes of your
graph
• create new ‘aggregator’ nodes and link your
node to them to better describe it
32. YOW building Links to other
nodes
... blah blah blah ...
... blah blah blah ...
... blah blah blah ...
A string +
some concept +
some couples
(property, value)
33. Proactive approach (2)
• An aggregator node can be anything that has
a DBpedia URI
• Ex.: Radiohead, The Name of the Rose, San
Francisco, Semantic Web, ...
• the link from a node to another or a smart tag
can have the name of a DBpedia property
• Ex.: language, genre, titleOrig, location, ...
34. Proactive approach (3)
Semtech 2008
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referring to DBpedia
not referring to anything WWW
35. Autocompletion support
• (URI, rdfs:label, skos:subject) and dbpprops
retrieved from SPARQL queries over DBpedia
• the most fitting subject, inspecting skos:subjects
and instances
• concepts ranked according to their pertinence to
other concepts the content node is linked to
• properties ranked according to concepts they
refer to
36. Lazy approach
• When you come across a web page with some
contents inserted in YOW, FOW (Friends’ Own
Web) and / or POW (Public Own Web):
• page contents present in YOW, FOW or POW
are highlighted
• page links that point to a page containing
some YOW, FOW or POW contents are
highlighted
37. Lazy approach (2)
• Each highlighted page item contains further info
about how many users chose it, who among your
friends, the best links inside their graphs,
comments, semantic categorization and an entry
to the relative graphs
• each highlighted link contains the same kind of
info, but referring to the content of the page the
link points to.
38. Proactive + lazy
socially
enabled
• Browse from your graph to others’ graphs by
nodes similarity
• Receive suggestions about new nodes/links to
add to your graph
• Suggest/comment on some nodes to friends
• Find new interesting nodes/friends
39. Now just begin to play..
michele.minno@asemantics.com
davide@asemantics.com
